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encode-chrombpnet-DNASE-posterior-cingulate-gyrus-ENCSR433NEX-ENCSR150BEX

chrombpnet
encode
chromatin-accessibility
DNASE
gyrus
hg38
Model card Files
xet
 Community
chang-m-yun commited on
Commit
30ac641
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1 Parent(s): de0e28c

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  1. .gitattributes +4 -0
  2. fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.batch_loss.tsv +0 -0
  3. fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.bias_formatting.stderr.txt +38 -0
  4. fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.bias_formatting.stdout.txt +1 -0
  5. fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet.params.json +11 -0
  6. fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet_data_params.tsv +3 -0
  7. fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet_formatting.stderr.txt +40 -0
  8. fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet_formatting.stdout.txt +1 -0
  9. fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet_model_params.tsv +9 -0
  10. fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  11. fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  12. fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.stdout.txt +3 -0
  13. fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.stdout_v1.txt +3 -0
  14. fold_0/model.bias_scaled.fold_0.ENCSR433NEX.h5 +3 -0
  15. fold_0/model.bias_scaled.fold_0.ENCSR433NEX.tar +3 -0
  16. fold_0/model.chrombpnet.fold_0.ENCSR433NEX.h5 +3 -0
  17. fold_0/model.chrombpnet.fold_0.ENCSR433NEX.tar +3 -0
  18. fold_0/model.chrombpnet_nobias.fold_0.ENCSR433NEX.h5 +3 -0
  19. fold_0/model.chrombpnet_nobias.fold_0.ENCSR433NEX.tar +3 -0
  20. fold_1/model.bias_scaled.fold_1.ENCSR433NEX.h5 +3 -0
  21. fold_1/model.bias_scaled.fold_1.ENCSR433NEX.tar +3 -0
  22. fold_1/model.chrombpnet.fold_1.ENCSR433NEX.h5 +3 -0
  23. fold_1/model.chrombpnet.fold_1.ENCSR433NEX.tar +3 -0
  24. fold_1/model.chrombpnet_nobias.fold_1.ENCSR433NEX.h5 +3 -0
  25. fold_1/model.chrombpnet_nobias.fold_1.ENCSR433NEX.tar +3 -0
  26. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.args.json +23 -0
  27. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.bias_formatting.stderr.txt +38 -0
  28. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.bias_formatting.stdout.txt +1 -0
  29. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.chrombpnet.params.json +11 -0
  30. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.chrombpnet_data_params.tsv +3 -0
  31. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.chrombpnet_formatting.stderr.txt +40 -0
  32. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.chrombpnet_formatting.stdout.txt +1 -0
  33. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.chrombpnet_no_bias_formatting.stderr.txt +1 -0
  34. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.chrombpnet_no_bias_formatting.stdout.txt +1 -0
  35. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.epoch_loss.csv +18 -0
  36. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.stderr.txt +332 -0
  37. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.stdout.txt +3 -0
  38. fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.stdout_v1.txt +3 -0
  39. fold_2/model.bias_scaled.fold_2.ENCSR433NEX.h5 +3 -0
  40. fold_2/model.bias_scaled.fold_2.ENCSR433NEX.tar +3 -0
  41. fold_2/model.chrombpnet.fold_2.ENCSR433NEX.h5 +3 -0
  42. fold_2/model.chrombpnet.fold_2.ENCSR433NEX.tar +3 -0
  43. fold_2/model.chrombpnet_nobias.fold_2.ENCSR433NEX.h5 +3 -0
  44. fold_2/model.chrombpnet_nobias.fold_2.ENCSR433NEX.tar +3 -0
  45. fold_3/logs.models.fold_3.ENCSR433NEX/logfile.modelling.fold_3.ENCSR433NEX.stdout_v1.txt +0 -0
  46. fold_3/model.bias_scaled.fold_3.ENCSR433NEX.h5 +3 -0
  47. fold_3/model.bias_scaled.fold_3.ENCSR433NEX.tar +3 -0
  48. fold_3/model.chrombpnet.fold_3.ENCSR433NEX.h5 +3 -0
  49. fold_3/model.chrombpnet.fold_3.ENCSR433NEX.tar +3 -0
  50. fold_3/model.chrombpnet_nobias.fold_3.ENCSR433NEX.h5 +3 -0
.gitattributes CHANGED
@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.stdout_v1.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.stdout.txt filter=lfs diff=lfs merge=lfs -text
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+ fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.stdout.txt filter=lfs diff=lfs merge=lfs -text
fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.batch_loss.tsv ADDED
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fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.bias_formatting.stderr.txt ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
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+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
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+ 2023-07-15 02:33:27.764998: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-15 02:33:30.051145: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
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+ 2023-07-15 02:33:30.054487: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
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+ 2023-07-15 02:33:30.685301: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
+ 2023-07-15 02:33:30.685415: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
10
+ 2023-07-15 02:33:30.708274: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
11
+ 2023-07-15 02:33:30.708357: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
12
+ 2023-07-15 02:33:30.717595: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-15 02:33:30.722003: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-15 02:33:30.737229: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-15 02:33:30.741331: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-15 02:33:30.742239: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-15 02:33:30.772814: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-15 02:33:30.773129: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
+ 2023-07-15 02:33:30.773984: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-15 02:33:30.794019: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:c3:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
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+ 2023-07-15 02:33:30.794050: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-15 02:33:30.794070: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+ 2023-07-15 02:33:30.794085: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-07-15 02:33:30.794099: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-15 02:33:30.794113: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-15 02:33:30.794126: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-15 02:33:30.794138: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-15 02:33:30.794151: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-15 02:33:30.821343: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-15 02:33:30.822630: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-15 02:33:33.776831: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-15 02:33:33.776898: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
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+ 2023-07-15 02:33:33.776912: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
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+ 2023-07-15 02:33:33.944251: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75650 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:c3:00.0, compute capability: 8.0)
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+ 2023-07-15 02:33:35.007435: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.bias_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
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+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR433NEX//chrombpnet_model_encsr880cub_bias/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR433NEX//chrombpnet_model_encsr880cub_bias/new_model_formats/bias_model_scaled
fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
2
+ "counts_loss_weight": "24.1",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR433NEX//chrombpnet_model_encsr880cub_bias/bias_model_scaled.h5",
6
+ "inputlen": "2114",
7
+ "outputlen": "1000",
8
+ "max_jitter": "500",
9
+ "chr_fold_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_0.json",
10
+ "negative_sampling_ratio": "0.1"
11
+ }
fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 10.0
2
+ counts_sum_max_thresh 3235.63
3
+ trainings_pts_post_thresh 171637
fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet_formatting.stderr.txt ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
2
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
+ 2023-07-15 01:31:49.559343: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
+ 2023-07-15 01:31:52.577529: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
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+ 2023-07-15 01:31:52.582178: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
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+ 2023-07-15 01:31:52.612334: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
7
+ pciBusID: 0000:04:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
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+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
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+ 2023-07-15 01:31:52.612423: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
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+ 2023-07-15 01:31:52.639036: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
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+ 2023-07-15 01:31:52.639131: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
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+ 2023-07-15 01:31:52.652602: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
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+ 2023-07-15 01:31:52.658630: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
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+ 2023-07-15 01:31:52.681945: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
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+ 2023-07-15 01:31:52.688113: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
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+ 2023-07-15 01:31:52.689377: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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+ 2023-07-15 01:31:52.694710: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
18
+ 2023-07-15 01:31:52.695089: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
+ 2023-07-15 01:31:52.696004: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
21
+ 2023-07-15 01:31:52.696283: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
22
+ pciBusID: 0000:04:00.0 name: Tesla P100-PCIE-16GB computeCapability: 6.0
23
+ coreClock: 1.3285GHz coreCount: 56 deviceMemorySize: 15.89GiB deviceMemoryBandwidth: 681.88GiB/s
24
+ 2023-07-15 01:31:52.696317: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
25
+ 2023-07-15 01:31:52.696351: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
26
+ 2023-07-15 01:31:52.696379: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
27
+ 2023-07-15 01:31:52.696406: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
28
+ 2023-07-15 01:31:52.696432: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
29
+ 2023-07-15 01:31:52.696468: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
30
+ 2023-07-15 01:31:52.696494: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
31
+ 2023-07-15 01:31:52.696519: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
32
+ 2023-07-15 01:31:52.696899: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
33
+ 2023-07-15 01:31:52.698286: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
34
+ 2023-07-15 01:31:54.596299: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
35
+ 2023-07-15 01:31:54.596392: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
36
+ 2023-07-15 01:31:54.596409: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
37
+ 2023-07-15 01:31:54.599584: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 14957 MB memory) -> physical GPU (device: 0, name: Tesla P100-PCIE-16GB, pci bus id: 0000:04:00.0, compute capability: 6.0)
38
+ 2023-07-15 01:31:56.991568: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
39
+ /opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/core.py:1059: UserWarning: is not loaded, but a Lambda layer uses it. It may cause errors.
40
+ , UserWarning)
fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR433NEX//chrombpnet_model_encsr880cub_bias/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR433NEX//chrombpnet_model_encsr880cub_bias/new_model_formats/chrombpnet
fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet_model_params.tsv ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ counts_loss_weight 24.1
2
+ filters 512
3
+ n_dil_layers 8
4
+ bias_model_path /scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR433NEX//chrombpnet_model_encsr880cub_bias/bias_model_scaled.h5
5
+ inputlen 2114
6
+ outputlen 1000
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+ max_jitter 500
8
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fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet_no_bias_formatting.stderr.txt ADDED
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fold_0/logs.models.fold_0.ENCSR433NEX/logfile.modelling.fold_0.ENCSR433NEX.chrombpnet_no_bias_formatting.stdout.txt ADDED
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21
+ "seed": 1234,
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23
+ }
fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.bias_formatting.stderr.txt ADDED
@@ -0,0 +1,38 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
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+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
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4
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6
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7
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8
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9
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10
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12
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14
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15
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16
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17
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18
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19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
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21
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22
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23
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24
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25
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26
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27
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28
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29
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30
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31
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32
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33
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34
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36
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38
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fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.bias_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR433NEX//chrombppnet_model_encsr880cub_bias_fold_2/bias_model_scaled.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR433NEX//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/bias_model_scaled
fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.chrombpnet.params.json ADDED
@@ -0,0 +1,11 @@
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "counts_loss_weight": "24.0",
3
+ "filters": "512",
4
+ "n_dil_layers": "8",
5
+ "bias_model_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR433NEX//chrombppnet_model_encsr880cub_bias_fold_2/bias_model_scaled.h5",
6
+ "inputlen": "2114",
7
+ "outputlen": "1000",
8
+ "max_jitter": "500",
9
+ "chr_fold_path": "/scratch/groups/akundaje/anusri/chromatin_atlas/splits/fold_2.json",
10
+ "negative_sampling_ratio": "0.1"
11
+ }
fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.chrombpnet_data_params.tsv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ counts_sum_min_thresh 14.0
2
+ counts_sum_max_thresh 3243.7
3
+ trainings_pts_post_thresh 177112
fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.chrombpnet_formatting.stderr.txt ADDED
@@ -0,0 +1,40 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
2
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
+ 2023-07-15 01:31:49.433528: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
4
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5
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6
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7
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8
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
9
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10
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11
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12
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13
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14
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15
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16
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17
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18
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19
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
20
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21
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22
+ pciBusID: 0000:45:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
23
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.15GiB deviceMemoryBandwidth: 1.85TiB/s
24
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25
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26
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27
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28
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29
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30
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31
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32
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33
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34
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36
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37
+ 2023-07-15 01:31:55.444573: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75650 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:45:00.0, compute capability: 8.0)
38
+ 2023-07-15 01:31:57.759515: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.
39
+ /opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/core.py:1059: UserWarning: is not loaded, but a Lambda layer uses it. It may cause errors.
40
+ , UserWarning)
fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.chrombpnet_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR433NEX//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR433NEX//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet
fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.chrombpnet_no_bias_formatting.stderr.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR433NEX//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR433NEX//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.chrombpnet_no_bias_formatting.stdout.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ singularity exec --nv /home/groups/akundaje/anusri/simg/tf-atlas_gcp-modeling.sif python get_new_tf_model_format.py -i /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR433NEX//chrombppnet_model_encsr880cub_bias_fold_2/chrombpnet_wo_bias.h5 -o /oak/stanford/groups/akundaje/projects/chromatin-atlas-2022/DNASE//ENCSR433NEX//chrombppnet_model_encsr880cub_bias_fold_2/new_model_formats/chrombpnet_wo_bias
fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.epoch_loss.csv ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ epoch,logcount_predictions_loss,logits_profile_predictions_loss,loss,val_logcount_predictions_loss,val_logits_profile_predictions_loss,val_loss
2
+ 0,0.5053864121437073,799.9454345703125,812.0731811523438,0.24753262102603912,848.2291259765625,854.1700439453125
3
+ 1,0.25790345668792725,778.7583618164062,784.9479370117188,0.24141904711723328,855.9481201171875,861.7426147460938
4
+ 2,0.24241924285888672,773.5743408203125,779.3921508789062,0.19167201220989227,844.3212280273438,848.9220581054688
5
+ 3,0.22273685038089752,772.0030517578125,777.3493041992188,0.1910877674818039,843.6948852539062,848.28076171875
6
+ 4,0.21801546216011047,768.5609130859375,773.7929077148438,0.1784640997648239,847.66162109375,851.9443359375
7
+ 5,0.21312972903251648,766.879150390625,771.993408203125,0.2047320306301117,844.951416015625,849.8651123046875
8
+ 6,0.20863525569438934,765.1143798828125,770.1218872070312,0.19007404148578644,843.3011474609375,847.8632202148438
9
+ 7,0.2012992799282074,763.1525268554688,767.9850463867188,0.18625012040138245,842.3240356445312,846.7943115234375
10
+ 8,0.19915637373924255,762.1785278320312,766.9601440429688,0.2013426423072815,847.3558959960938,852.1881103515625
11
+ 9,0.19576363265514374,760.6943359375,765.392333984375,0.1797408163547516,843.0657958984375,847.3792724609375
12
+ 10,0.19701969623565674,759.6556396484375,764.38623046875,0.17747734487056732,845.061279296875,849.3209838867188
13
+ 11,0.17902281880378723,752.5885009765625,756.8851928710938,0.17564159631729126,841.7664794921875,845.9818115234375
14
+ 12,0.17279531061649323,748.2981567382812,752.4451293945312,0.19915145635604858,842.3113403320312,847.0914916992188
15
+ 13,0.16935598850250244,745.9547729492188,750.0198364257812,0.1721171736717224,847.6805419921875,851.8115234375
16
+ 14,0.1698688417673111,742.6239624023438,746.701171875,0.16926270723342896,847.6592407226562,851.7210693359375
17
+ 15,0.16021403670310974,737.6986694335938,741.5442504882812,0.171507328748703,846.3475341796875,850.463623046875
18
+ 16,0.1602088361978531,735.5307006835938,739.3762817382812,0.17201535403728485,846.97900390625,851.1073608398438
fold_2/logs.models.fold_2.ENCSR433NEX/logfile.modelling.fold_2.ENCSR433NEX.stderr.txt ADDED
@@ -0,0 +1,332 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
2
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
3
+ INFO: underlay of /etc/localtime required more than 50 (88) bind mounts
4
+ INFO: underlay of /usr/bin/nvidia-smi required more than 50 (355) bind mounts
5
+ 2022-10-11 22:58:19.575959: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
6
+ 2022-10-11 23:04:35.179838: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
7
+ 2022-10-11 23:04:35.183789: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
8
+ 2022-10-11 23:04:35.514122: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
9
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
10
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
11
+ 2022-10-11 23:04:35.514232: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
12
+ 2022-10-11 23:04:35.532549: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
13
+ 2022-10-11 23:04:35.532625: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
14
+ 2022-10-11 23:04:35.542031: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
15
+ 2022-10-11 23:04:35.546497: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
16
+ 2022-10-11 23:04:35.561920: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
17
+ 2022-10-11 23:04:35.565977: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
18
+ 2022-10-11 23:04:35.566921: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
19
+ 2022-10-11 23:04:35.571070: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
20
+ 2022-10-11 23:04:35.571388: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
21
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
22
+ 2022-10-11 23:04:35.572060: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
23
+ 2022-10-11 23:04:35.573660: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
24
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
25
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
26
+ 2022-10-11 23:04:35.573688: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
27
+ 2022-10-11 23:04:35.573705: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
28
+ 2022-10-11 23:04:35.573718: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
29
+ 2022-10-11 23:04:35.573730: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
30
+ 2022-10-11 23:04:35.573741: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
31
+ 2022-10-11 23:04:35.573753: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
32
+ 2022-10-11 23:04:35.573765: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
33
+ 2022-10-11 23:04:35.573776: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
34
+ 2022-10-11 23:04:35.576913: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
35
+ 2022-10-11 23:04:35.577935: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
36
+ 2022-10-11 23:04:36.935435: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
37
+ 2022-10-11 23:04:36.950056: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
38
+ 2022-10-11 23:04:36.950076: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
39
+ 2022-10-11 23:04:36.955604: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:41:00.0, compute capability: 8.0)
40
+ 2022-10-11 23:04:38.665533: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
41
+ 2022-10-11 23:04:38.677167: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794600000 Hz
42
+ 2022-10-11 23:04:38.837760: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
43
+ 2022-10-11 23:04:40.177847: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
44
+ 2022-10-11 23:04:40.184919: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
45
+ 2022-10-11 23:05:10.315695: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
46
+ 2022-10-11 23:05:11.884601: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
47
+ 2022-10-11 23:05:11.885413: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
48
+ 2022-10-11 23:05:12.085346: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
49
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
50
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
51
+ 2022-10-11 23:05:12.085456: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
52
+ 2022-10-11 23:05:12.087613: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
53
+ 2022-10-11 23:05:12.087658: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
54
+ 2022-10-11 23:05:12.088609: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
55
+ 2022-10-11 23:05:12.088873: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
56
+ 2022-10-11 23:05:12.090879: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
57
+ 2022-10-11 23:05:12.091385: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
58
+ 2022-10-11 23:05:12.091639: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
59
+ 2022-10-11 23:05:12.093225: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
60
+ 2022-10-11 23:05:12.093508: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
61
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
62
+ 2022-10-11 23:05:12.093569: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
63
+ 2022-10-11 23:05:12.094380: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
64
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
65
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
66
+ 2022-10-11 23:05:12.094402: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
67
+ 2022-10-11 23:05:12.094418: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
68
+ 2022-10-11 23:05:12.094432: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
69
+ 2022-10-11 23:05:12.094444: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
70
+ 2022-10-11 23:05:12.094456: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
71
+ 2022-10-11 23:05:12.094467: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
72
+ 2022-10-11 23:05:12.094479: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
73
+ 2022-10-11 23:05:12.094490: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
74
+ 2022-10-11 23:05:12.095981: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
75
+ 2022-10-11 23:05:12.096010: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
76
+ 2022-10-11 23:05:12.558872: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
77
+ 2022-10-11 23:05:12.558999: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
78
+ 2022-10-11 23:05:12.559012: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
79
+ 2022-10-11 23:05:12.561681: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:41:00.0, compute capability: 8.0)
80
+ 2022-10-11 23:12:09.967471: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
81
+ 2022-10-11 23:12:09.977262: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794600000 Hz
82
+ 2022-10-11 23:12:11.288170: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
83
+ 2022-10-11 23:12:11.710593: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
84
+ 2022-10-11 23:12:11.724930: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
85
+ 2022-10-11 23:12:14.990154: I tensorflow/stream_executor/cuda/cuda_blas.cc:1838] TensorFloat-32 will be used for the matrix multiplication. This will only be logged once.
86
+ 2022-10-12 01:00:56.334831: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
87
+ 2022-10-12 01:00:58.904966: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
88
+ 2022-10-12 01:00:58.906174: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
89
+ 2022-10-12 01:00:59.085041: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
90
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
91
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
92
+ 2022-10-12 01:00:59.085153: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
93
+ 2022-10-12 01:00:59.087550: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
94
+ 2022-10-12 01:00:59.087617: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
95
+ 2022-10-12 01:00:59.088695: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
96
+ 2022-10-12 01:00:59.089028: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
97
+ 2022-10-12 01:00:59.091134: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
98
+ 2022-10-12 01:00:59.091686: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
99
+ 2022-10-12 01:00:59.092017: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
100
+ 2022-10-12 01:00:59.093642: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
101
+ 2022-10-12 01:00:59.093948: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
102
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
103
+ 2022-10-12 01:00:59.094011: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
104
+ 2022-10-12 01:00:59.094830: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
105
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
106
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
107
+ 2022-10-12 01:00:59.094863: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
108
+ 2022-10-12 01:00:59.094883: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
109
+ 2022-10-12 01:00:59.094899: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
110
+ 2022-10-12 01:00:59.094913: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
111
+ 2022-10-12 01:00:59.094927: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
112
+ 2022-10-12 01:00:59.094941: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
113
+ 2022-10-12 01:00:59.094954: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
114
+ 2022-10-12 01:00:59.094967: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
115
+ 2022-10-12 01:00:59.096482: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
116
+ 2022-10-12 01:00:59.096510: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
117
+ 2022-10-12 01:00:59.562861: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
118
+ 2022-10-12 01:00:59.562970: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
119
+ 2022-10-12 01:00:59.562983: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
120
+ 2022-10-12 01:00:59.565625: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:41:00.0, compute capability: 8.0)
121
+ 2022-10-12 01:02:19.147133: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
122
+ 2022-10-12 01:02:19.149954: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794600000 Hz
123
+ 2022-10-12 01:02:19.221257: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
124
+ 2022-10-12 01:02:19.660580: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
125
+ 2022-10-12 01:02:19.662463: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
126
+ /opt/conda/lib/python3.7/site-packages/tensorflow/python/keras/layers/core.py:1059: UserWarning: is not loaded, but a Lambda layer uses it. It may cause errors.
127
+ , UserWarning)
128
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
129
+ cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
130
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
131
+ profile_prob = profile / np.sum(profile)
132
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
133
+ shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
134
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
135
+ curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
136
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
137
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
138
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
139
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
140
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
141
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
142
+ 2022-10-12 01:04:10.909994: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
143
+ 2022-10-12 01:04:13.148524: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
144
+ 2022-10-12 01:04:13.149523: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
145
+ 2022-10-12 01:04:13.353141: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
146
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
147
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
148
+ 2022-10-12 01:04:13.353243: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
149
+ 2022-10-12 01:04:13.355484: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
150
+ 2022-10-12 01:04:13.355534: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
151
+ 2022-10-12 01:04:13.356509: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
152
+ 2022-10-12 01:04:13.356774: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
153
+ 2022-10-12 01:04:13.358878: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
154
+ 2022-10-12 01:04:13.359388: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
155
+ 2022-10-12 01:04:13.359686: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
156
+ 2022-10-12 01:04:13.361324: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
157
+ 2022-10-12 01:04:13.361626: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
158
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
159
+ 2022-10-12 01:04:13.361684: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
160
+ 2022-10-12 01:04:13.362485: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
161
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
162
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
163
+ 2022-10-12 01:04:13.362507: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
164
+ 2022-10-12 01:04:13.362524: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
165
+ 2022-10-12 01:04:13.362538: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
166
+ 2022-10-12 01:04:13.362551: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
167
+ 2022-10-12 01:04:13.362563: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
168
+ 2022-10-12 01:04:13.362575: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
169
+ 2022-10-12 01:04:13.362587: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
170
+ 2022-10-12 01:04:13.362599: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
171
+ 2022-10-12 01:04:13.364108: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
172
+ 2022-10-12 01:04:13.364136: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
173
+ 2022-10-12 01:04:13.851361: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
174
+ 2022-10-12 01:04:13.851473: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
175
+ 2022-10-12 01:04:13.851485: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
176
+ 2022-10-12 01:04:13.854397: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:41:00.0, compute capability: 8.0)
177
+ WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
178
+ 2022-10-12 01:05:23.445573: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
179
+ 2022-10-12 01:05:23.447512: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794600000 Hz
180
+ 2022-10-12 01:05:23.493071: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
181
+ 2022-10-12 01:05:23.954267: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
182
+ 2022-10-12 01:05:23.955701: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
183
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
184
+ cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
185
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
186
+ profile_prob = profile / np.sum(profile)
187
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
188
+ shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
189
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
190
+ curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
191
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
192
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
193
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
194
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
195
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
196
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
197
+ 2022-10-12 01:07:07.196292: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
198
+ 2022-10-12 01:07:09.475112: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
199
+ 2022-10-12 01:07:09.476154: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
200
+ 2022-10-12 01:07:09.676604: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
201
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
202
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
203
+ 2022-10-12 01:07:09.676717: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
204
+ 2022-10-12 01:07:09.679009: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
205
+ 2022-10-12 01:07:09.679075: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
206
+ 2022-10-12 01:07:09.680112: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
207
+ 2022-10-12 01:07:09.680422: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
208
+ 2022-10-12 01:07:09.682548: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
209
+ 2022-10-12 01:07:09.683099: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
210
+ 2022-10-12 01:07:09.683411: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
211
+ 2022-10-12 01:07:09.685046: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
212
+ 2022-10-12 01:07:09.685339: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
213
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
214
+ 2022-10-12 01:07:09.685405: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
215
+ 2022-10-12 01:07:09.686229: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
216
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
217
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
218
+ 2022-10-12 01:07:09.686250: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
219
+ 2022-10-12 01:07:09.686291: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
220
+ 2022-10-12 01:07:09.686309: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
221
+ 2022-10-12 01:07:09.686324: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
222
+ 2022-10-12 01:07:09.686339: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
223
+ 2022-10-12 01:07:09.686353: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
224
+ 2022-10-12 01:07:09.686367: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
225
+ 2022-10-12 01:07:09.686381: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
226
+ 2022-10-12 01:07:09.687927: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
227
+ 2022-10-12 01:07:09.687965: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
228
+ 2022-10-12 01:07:10.170244: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
229
+ 2022-10-12 01:07:10.170356: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
230
+ 2022-10-12 01:07:10.170370: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
231
+ 2022-10-12 01:07:10.172996: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:41:00.0, compute capability: 8.0)
232
+ 2022-10-12 01:08:20.829377: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
233
+ 2022-10-12 01:08:20.830880: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794600000 Hz
234
+ 2022-10-12 01:08:20.862130: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
235
+ 2022-10-12 01:08:21.320520: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
236
+ 2022-10-12 01:08:21.321920: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
237
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:69: RuntimeWarning: invalid value encountered in true_divide
238
+ cur_jsd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),pred_probs[idx,:])
239
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/utils/metrics_utils.py:196: RuntimeWarning: invalid value encountered in true_divide
240
+ profile_prob = profile / np.sum(profile)
241
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:78: RuntimeWarning: invalid value encountered in true_divide
242
+ shuffled_labels_prob=shuffled_labels/np.nansum(shuffled_labels)
243
+ /home/users/anusri/chromatin-atlas-anvil/sherlock/chrombpnet/src/training/metrics.py:88: RuntimeWarning: invalid value encountered in true_divide
244
+ curr_jsd_rnd=jensenshannon(true_counts[idx,:]/np.nansum(true_counts[idx,:]),shuffled_labels_prob)
245
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
246
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
247
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
248
+ findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.
249
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
250
+ No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.
251
+ 2022-10-12 01:09:15.263264: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
252
+ 2022-10-12 01:09:16.381250: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
253
+ 2022-10-12 01:09:16.382204: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
254
+ 2022-10-12 01:09:16.580640: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
255
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
256
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
257
+ 2022-10-12 01:09:16.580753: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
258
+ 2022-10-12 01:09:16.582989: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
259
+ 2022-10-12 01:09:16.583040: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
260
+ 2022-10-12 01:09:16.584018: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
261
+ 2022-10-12 01:09:16.584276: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
262
+ 2022-10-12 01:09:16.586346: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
263
+ 2022-10-12 01:09:16.586875: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
264
+ 2022-10-12 01:09:16.587168: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
265
+ 2022-10-12 01:09:16.588772: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
266
+ 2022-10-12 01:09:16.589060: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
267
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
268
+ 2022-10-12 01:09:16.589120: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
269
+ 2022-10-12 01:09:16.589914: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
270
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
271
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
272
+ 2022-10-12 01:09:16.589943: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
273
+ 2022-10-12 01:09:16.589962: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
274
+ 2022-10-12 01:09:16.589978: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
275
+ 2022-10-12 01:09:16.589993: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
276
+ 2022-10-12 01:09:16.590006: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
277
+ 2022-10-12 01:09:16.590020: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
278
+ 2022-10-12 01:09:16.590033: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
279
+ 2022-10-12 01:09:16.590047: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
280
+ 2022-10-12 01:09:16.591576: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
281
+ 2022-10-12 01:09:16.591611: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
282
+ 2022-10-12 01:09:17.067207: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
283
+ 2022-10-12 01:09:17.067316: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
284
+ 2022-10-12 01:09:17.067329: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
285
+ 2022-10-12 01:09:17.070019: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:41:00.0, compute capability: 8.0)
286
+ WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.
287
+ 2022-10-12 01:09:33.168006: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
288
+ 2022-10-12 01:09:33.168523: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794600000 Hz
289
+ 2022-10-12 01:09:33.343034: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
290
+ 2022-10-12 01:09:33.858470: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
291
+ 2022-10-12 01:09:33.860081: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
292
+ mkdir: cannot create directory ‘/scratch/groups/akundaje/anusri/chromatin_atlas/DNASE/ENCSR433NEX//chrombppnet_model_encsr880cub_bias_fold_2//footprints’: File exists
293
+ 2022-10-12 01:11:14.238741: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
294
+ 2022-10-12 01:11:15.336591: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
295
+ 2022-10-12 01:11:15.337520: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
296
+ 2022-10-12 01:11:15.538679: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
297
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
298
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
299
+ 2022-10-12 01:11:15.538794: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
300
+ 2022-10-12 01:11:15.540957: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
301
+ 2022-10-12 01:11:15.541008: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
302
+ 2022-10-12 01:11:15.542004: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
303
+ 2022-10-12 01:11:15.542271: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
304
+ 2022-10-12 01:11:15.544345: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
305
+ 2022-10-12 01:11:15.544865: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
306
+ 2022-10-12 01:11:15.545164: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
307
+ 2022-10-12 01:11:15.546791: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
308
+ 2022-10-12 01:11:15.547093: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
309
+ To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
310
+ 2022-10-12 01:11:15.547182: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
311
+ 2022-10-12 01:11:15.547998: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
312
+ pciBusID: 0000:41:00.0 name: NVIDIA A100-SXM4-80GB computeCapability: 8.0
313
+ coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 79.21GiB deviceMemoryBandwidth: 1.85TiB/s
314
+ 2022-10-12 01:11:15.548027: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
315
+ 2022-10-12 01:11:15.548044: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
316
+ 2022-10-12 01:11:15.548058: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
317
+ 2022-10-12 01:11:15.548070: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
318
+ 2022-10-12 01:11:15.548083: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
319
+ 2022-10-12 01:11:15.548096: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
320
+ 2022-10-12 01:11:15.548108: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
321
+ 2022-10-12 01:11:15.548120: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
322
+ 2022-10-12 01:11:15.549627: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0
323
+ 2022-10-12 01:11:15.549662: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
324
+ 2022-10-12 01:11:16.029039: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
325
+ 2022-10-12 01:11:16.029149: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
326
+ 2022-10-12 01:11:16.029162: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
327
+ 2022-10-12 01:11:16.031848: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 75712 MB memory) -> physical GPU (device: 0, name: NVIDIA A100-SXM4-80GB, pci bus id: 0000:41:00.0, compute capability: 8.0)
328
+ 2022-10-12 01:11:32.150362: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
329
+ 2022-10-12 01:11:32.150890: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 2794600000 Hz
330
+ 2022-10-12 01:11:32.274144: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
331
+ 2022-10-12 01:11:32.795199: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
332
+ 2022-10-12 01:11:32.796741: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
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